Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Data Manipulation f

Recommender Systems Complete Course Beginner to Advanced - Machine Learning for Recommender Systems: Data Manipulation f

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video tutorial explains how to extract titles and years from a movie dataset using Python. It covers creating functions to separate titles from years, handling cases where years are missing, and applying these functions to a dataset. The tutorial also discusses renaming columns and checking for missing values, providing a comprehensive guide to processing movie data.

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10 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the first step in extracting the title from the data?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

How do we differentiate between the year and the title in the dataset?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What should be done if a movie does not have a year in the dataset?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

How do we extract the year from the title?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the purpose of the if statement when checking the year?

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6.

OPEN ENDED QUESTION

3 mins • 1 pt

What happens if the year is not numeric?

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7.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the two functions discussed for extracting titles and years?

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